This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem b...
We present new insights into how to achieve higher frequencies in large-scale nonlinear predictive control using truncated-like schemes. The basic idea is that, instead of solving ...
We present two complementary methods for automatically improving mesh parameterizations and demonstrate that they provide a very desirable combination of efficiency and quality. ...
Abstract: It is often challenging to reconstruct accurately a complete dynamic biological network due to the scarcity of data collected in cost-effective experiments. This paper ad...
Off-line robot dynamic identification methods are mostly based on the use of the inverse dynamic model, which is linear with respect to the dynamic parameters. This model is sample...
Maxime Gautier, Alexandre Janot, Pierre-Olivier Va...